As wireless communication systems proliferate worldwide, complicated signal environments are bound to occur, which may cause signal interference to increase. Thus, there is often a need to provide interference mitigation in wireless networks.
Current methods for handling interference in wireless networks depend on the specific attributes of the network. For traditional cellular networks, interference mitigation techniques include power-control, frequency reuse, and fine-grained rate control based on channel-quality measurements. Additionally, cellular networks often require some aspect of central planning in order to effectively apply the aforementioned techniques. For ad-hoc networks, especially those running the 802.11 protocol, interference is typically mitigated using a distributed collision-based random access scheme. These collision-based random access schemes may be coupled with a coarse-grained rate-adaptation procedure.
However, it is difficult to mitigate interference in cellular systems with distributed components, such as heterogeneous 4G LTE (also known as Long Term Evolution) cellular network systems that also include smallcells. In this context, smallcells may be base stations that aim to provide high data rate coverage over a small high-traffic area. Examples of smallcells include picocells and femtocells.
Picocells are small cellular base stations that are typically used to extend coverage to indoor areas with weak outdoor signal coverage, or to add network capacity to indoor areas with very dense phone usage. Picocells are often placed inside buildings (e.g., offices, shopping centers, train stations, and the like) or inside aircraft. In many cases, picocells are owned by a cellular provider and placed in public locations. Alternatively, femtocells are low power cellular base stations that are typically owned by a private entity with the aim of improving coverage in a private location, such as a home or business. Because femtocells are often used by private entities, they can operate in Closed Subscriber Group (CSG) mode, where the base station restricts the set of mobile terminals that can connect to the femtocell.
Furthermore, smallcells may cause interference with user terminals that are operating in a macrocell. A macrocell is a cell in a mobile phone network that provides radio coverage served by a high power cellular base station. Interference to macrocell users may come from neighboring smallcells, or from smallcells that operate in the interior of the macrocell.
However, traditional interference mitigation techniques are difficult to implement because LTE networks with smallcells represent a hybrid of traditional cellular networks and traditional ad-hoc networks. On the one hand, base stations run LTE protocols that may provide for one or more interference mitigation schemes. On the other hand, the placement of smallcells in an LTE network is likely to be unstructured and so the interference configurations are likely to resemble a typical ad-hoc configuration. As a consequence, centralized planning of the placement of smallcells is unlikely.
Prior interference mitigation techniques mainly fall into two categories, resource allocation in orthogonal frequency-division multiplexing (OFDM) systems and Carrier Sense Multiple Access (CSMA) based algorithms for 802.11 networks.
Resource allocation in OFDM systems addresses problems such as channel selection, local scheduling, power control and user association (i.e. which base station serves which user). One popular technique is a Gibbs sampler approach based on Interacting Particle Systems. The premise of the Gibbs sampler approach is that for a given network configuration each node has a local energy based on the interference that it both causes and receives. Nodes then pick new states based on their local energy. Gibbs sampler techniques have also been used to motivate greedy algorithms for LTE carrier selection. Another popular OFDM technique is to set power levels according to a gradient ascent approach. In particular, each transmitter adjusts power levels so as to improve network utility in its neighborhood. Both the Gibbs sampler and the gradient ascent methods require information exchange on how much interference each transmitter causes to each receiver. For the Gibbs sampler methods, interference information needs to be exchanged in order to calculate local energy levels. For the gradient ascent methods, nodes need to exchange “partial derivative” information to indicate how the interference they experience would be affected by a change in a neighbor's power levels.
In CSMA networks, all user terminals wish to access a single channel. To achieve this end, a transmitter tries to detect the presence of an encoded signal from another station before attempting to transmit. If a carrier is sensed, the station waits for the transmission in progress to finish before initiating its own transmission. However, most CSMA interference mitigation techniques require channel access rates that depend on local queue sizes in order to keep the system stable.